colorcet:CET_D4#
Aliases: colorcet:d04, colorcet:d4, colorcet:bkr, colorcet:diverging_bkr_55_10_c35_n256
Diverging blue - black - red colour map
| collection | category | license | authors | source |
|---|---|---|---|---|
| colorcet | Diverging | CC-BY-4.0 | Peter Kovesi | https://colorcet.com |
from cmap import Colormap
cm = Colormap("colorcet:CET_D4") # case insensitive
import matplotlib.pyplot as plt
from cmap import Colormap
plt.imshow(data, cmap=Colormap("colorcet:CET_D4").to_mpl())
import plotly.express as px
from cmap import Colormap
px.imshow(data, color_continuous_scale=Colormap("colorcet:CET_D4").to_plotly())
import napari
from cmap import Colormap
napari.imshow(data, colormap=Colormap("colorcet:CET_D4").to_napari())
napari.run()
background: #1981FA;
background: linear-gradient(90deg, #1981FA 0%, #237AEA 3.22581%, #2973DA 6.45161%, #2D6CCA 9.67742%, #2F65BB 12.9032%, #315EAC 16.129%, #32579D 19.3548%, #32508E 22.5806%, #314A7F 25.8065%, #304371 29.0323%, #2E3D63 32.2581%, #2C3755 35.4839%, #293048 38.7097%, #262A3B 41.9355%, #22252F 45.1613%, #212024 48.3871%, #251F1F 51.6129%, #2F2220 54.8387%, #3B2622 58.0645%, #472924 61.2903%, #542D27 64.5161%, #603129 67.7419%, #6D342B 70.9677%, #79372E 74.1935%, #863B30 77.4194%, #943E33 80.6452%, #A14135 83.871%, #AE4438 87.0968%, #BC473A 90.3226%, #CA4A3D 93.5484%, #D84D3F 96.7742%, #E65041 100%);
import altair as alt
from cmap import Colormap
# df: a DataFrame with columns x, y and value
alt.Chart(df).mark_rect().encode(
x="x:O",
y="y:O",
color=alt.Color(
"value:Q", scale=alt.Scale(range=Colormap("colorcet:CET_D4").to_altair())
),
)
from bokeh.plotting import figure, show
from cmap import Colormap
p = figure()
p.image(
image=[data], x=0, y=0, dw=1, dh=1,
color_mapper=Colormap("colorcet:CET_D4").to_bokeh(),
)
show(p)
from vispy import app, scene
from cmap import Colormap
canvas = scene.SceneCanvas(show=True)
view = canvas.central_widget.add_view()
scene.visuals.Image(data, cmap=Colormap("colorcet:CET_D4").to_vispy(), parent=view.scene)
view.camera = scene.PanZoomCamera(aspect=1)
view.camera.set_range()
app.run()
import pygfx as gfx
from cmap import Colormap
image = gfx.Image(
gfx.Geometry(grid=gfx.Texture(data, dim=2)),
gfx.ImageBasicMaterial(
clim=(data.min(), data.max()), map=Colormap("colorcet:CET_D4").to_pygfx()
),
)
gfx.show(image)
import pyqtgraph as pg
from cmap import Colormap
view = pg.image(data)
view.setColorMap(Colormap("colorcet:CET_D4").to_pyqtgraph())
pg.exec()
import ee
from cmap import Colormap
ee.Initialize(project="my-project") # your Google Cloud project
elevation = ee.Image("CGIAR/SRTM90_V4")
image = elevation.visualize(
min=0, max=3000, palette=Colormap("colorcet:CET_D4").to_gee()
)
See also usage with external libraries.
colorcet:CET_D4
colorcet:CET_D4
Perceptual lightness#
Lightness (J′) measured in CAM02 Uniform Color Space (CAM02-UCS)